{"id":1226842,"url":"https://alion.io/job/idfc-senior-data-engineer","title":"Senior Data Engineer","company":{"id":1860009,"name":"IDFC","domain":"idfc.org","url":"https://alion.io/company/idfc","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":23000,"max_usd":47000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":56},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Hadoop","optional":false},{"name":"HBase","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-09-23T19:16:08Z","employer_posted_date":null,"last_verified_at":"2026-09-23T19:16:08Z","board_verified":false,"closed_at":null,"days_open":18,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":18},"description":"Job Requirements\n\nAbout the Role\n\nAs a Senior Data Engineer in the New Age Data & Analytics team at IDFC FIRST Bank, you will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure to support advanced analytics and business intelligence. This role demands deep technical expertise in big data technologies, cloud platforms, and data architecture. You will also lead engineering initiatives, collaborate with cross-functional teams, and contribute to enterprise-wide data strategy and innovation.\n\nKey Responsibilities\n\nPrimary Responsibilities\n\nDesign and develop scalable data pipelines across the full data lifecycle—from ingestion and transformation to consumption.\nWork with large-scale data volumes (TBs/PBs) and ensure efficient data processing and storage.\nCollaborate with business stakeholders to identify high-impact problems and translate them into data solutions.\nApply advanced knowledge of SQL, Spark, Python, Scala, and the Hadoop ecosystem.\nImplement and manage Data Lake/Lakehouse architectures using platforms like Cloudera, Hortonworks, and AWS.\nDevelop APIs and integrate them into data workflows for seamless data access and usability.\nUtilize big data infrastructure tools including Spark Streaming, EMR, MapReduce, Hive, HDFS, YARN, HBase, and Oozie.\nCreate and maintain technical design documentation (HLD/LLD) for data pipelines and architecture.\nDebug and resolve technical issues in data architecture and ensure high availability and performance.\n\nSecondary Responsibilities\n\nWork independently and manage your own development efforts.\nCollaborate with BI analysts and engineers to prototype and implement analytical models.\nIdentify key performance indicators and define strategies to meet analytical goals.\nPresent data solutions and insights to stakeholders and leadership teams.\n\nManagerial & Leadership Responsibilities\n\nLead moderately complex data engineering initiatives aligned with enterprise strategy.\nBuild and maintain optimized, highly available data pipelines to support analytics and reporting.\nOversee data integration efforts, including modeling, warehousing, and analytics environments.\nResolve complex data engineering issues while ensuring compliance with data governance policies.\nCollaborate with peers and managers to align on strategic goals and deliverables.\n\nWhat We Are Looking For\n\nEducation\n\nBachelor's degree in computer science or information technology or engineering\n\nExperience\n\n6+ years of experience in data engineering, with at least 3 years in large-scale Data Lake ecosystems.\n\nSkills and Attributes\n\nProven expertise in SQL, Spark, Python, Scala, and big data tools.\nStrong understanding of Data Lake/Lakehouse architecture and cloud platforms (especially AWS).\nExperience with machine learning frameworks and real-time data processing.\nDeep knowledge of relational and non-relational databases and data mining techniques.\nStrong debugging and problem-solving skills.\nExcellent communication and documentation abilities.\nAbility to lead technical projects and mentor junior engineers.\n\nKey Success Metrics\n\nTimely and error-free delivery of data engineering projects.\nIdentification and resolution of data issues.\nLeadership in technical aspects of data initiatives.\nHigh performance and availability of data 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